Robust Monopoly Regulation
研究如何用稳健设计（非贝叶斯方法）监管垄断企业，推导出最小化监管者最坏情况遗憾的政策，包括平均收入上限和按件补贴等工具。
We study how to regulate a monopolistic firm using a robust-design, non-Bayesian approach. We derive a policy that minimizes the regulator’s worst-case regret, where regret is the difference between the regulator’s complete-information payoff and his realized payoff. When the regulator’s payoff is consumers’ surplus, he caps the firm’s average revenue. When his payoff is the total surplus of both consumers and the firm, he offers a piece rate subsidy to the firm while capping the total subsidy. For intermediate cases, the regulator combines these three policy instruments to balance three goals: protecting consumers’ surplus, mitigating underproduction, and limiting potential overproduction.